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On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting., , , и . NeurIPS, (2022)Aligning Language Models with Preferences through f-divergence Minimization., , , , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 11546-11583. PMLR, (2023)Fine-Tuning Tree-LSTM for Phrase-Level Sentiment Classification on a Polish Dependency Treebank., и . LCT, том 12598 из Lecture Notes in Computer Science, стр. 31-42. Springer, (2017)Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback., , , , , , , , , и 22 other автор(ы). Trans. Mach. Learn. Res., (2023)The Reversal Curse: LLMs trained on Ä is B" fail to learn "B is A"., , , , , , и . ICLR, OpenReview.net, (2024)RL with KL penalties is better viewed as Bayesian inference., , и . EMNLP (Findings), стр. 1083-1091. Association for Computational Linguistics, (2022)Controlling Conditional Language Models without Catastrophic Forgetting., , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 11499-11528. PMLR, (2022)The Emergence of Action-grounded Compositional Communication., , , , , и . CogSci, cognitivesciencesociety.org, (2020)Taken out of context: On measuring situational awareness in LLMs., , , , , , , и . CoRR, (2023)Towards Understanding Sycophancy in Language Models., , , , , , , , , и 8 other автор(ы). ICLR, OpenReview.net, (2024)